IMPLEMENTATION OF WHOLE GENOME SELECTION IN THE U.S. BEEF CATTLE INDUSTRIES
Bovine Functional Genomics
2010 Annual Report
1a.Objectives (from AD-416)
Use the BovineSNP50 assay to provide high-accuracy predictions of genetic merit to U.S. beef breeds;.
2)Enable the adoption of whole genome enabled animal selection (WGEAS) by developing low-density and low-cost SNP assays for: a) intermediate-accuracy genetic prediction, b) mate selection, and c) parentage verification and traceability;.
3)Develop, adapt and optimize statistical methodologies to: a) fully integrate SNP genotype or haplotype effects into existing genetic evaluation technologies, and b) supplement or replace pedigree data; and.
4)Collaborate and coordinate U.S. and European Union WGEAS activities.
1b.Approach (from AD-416)
Genetic prediction using high-density SNP data will be implemented using MTDFREML. Implementation of more sophisticated strategies will follow using the MTGSAM programs that will be modified to accommodate extensions to the prediction model. Collaboration with a biotechnology company to develop a 384-SNP assay that is expected to dramatically decrease genotyping costs and increase sample throughput. A machine learning approach using a two-step feature subset selection algorithm will be evaluated for SNP selection for this assay.
Develop BLUP approaches for the prediction of genetic merit in non-pedigreed populations using molecular relationship matrices.
We shall manage this coordination and collaboration via e-mail and teleconference calls, however, we shall also meet at least annually in conjunction with the PAG or ISAG meetings alternating between the US and Europe to coordinate activities.
The number of SNPs required to estimate the genomic relationship matrix was examined in a group of 698 Angus steers with individual feed intake data and that were sired by 100 Angus AI bulls. In this study, several strategies were examined for the selection of reduced subsets of SNPs from random sampling to trait-associated SNPs. Results showed that genome enhanced predicted breeding values (GEPBVs) computed using genomic relationship matrices estimated from at least 10,000 SNPs were very robust. However, the accuracy of GEPBVs declined rapidly as the number of SNPs used to compute the genomic relationship matrix declined below 2,500. This suggests that reduced marker panels of about 3,000 SNPs will have great utility for the implementation of WGEAS in the U.S. beef and dairy industries if these assays can be delivered at reagent prices of about $25 per sample. Monitoring activities associated with this project included regular email correspondence and conference calls. This research supports the related in-house project to use genotypic data and resulting bovine haplotype map to enhance genetic improvement in dairy cattle through development and implementation of whole genome selection and enhanced parentage verification approaches (obj. #2).